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Meaningful Graphs is a concise and practical go-to guide for creating charts in Excel (r) that clearly and accurately tell the story in your data. It incorporates (a) explanations of the graph design principles of the experts (Tufte, Few, Robbins, Zelazny, and others), (b) the software steps necessary to incorporate these principles into Excel (r) charts, and (c) chart-related discussions of quality improvement (including Pareto charts), statistics (including run charts and correlations), and the use of graphs in PowerPoint (r) presentations (including chart animation). Also included are numerous "Tips" and "In Practice" examples drawn from over 35 years of working with data in healthcare settings. Coverage begins with highlighting the importance of knowing the story in your data and general principles of chart design (e.g., chartjunk, the use of color, consideration of three dimensional charts) and then proceeds to examine and create the five major chart types (column, bar, line, pie, scatter). This is followed by considerations of the pros and cons of each of the six less frequently employed chart types. There are over 120 graphs in full color plus tables and illustrations. Discussions of the most useful chart types include examples with accompanying data to facilitate practice. While illustrations are especially tailored for healthcare professionals (physicians, nurses, patient safety, quality improvement staff, executives, and managers) both in their work setting and in their academic preparation, the principles of graph design and the Excel (r) techniques required to incorporate these principles apply equally well in other settings. The latter include other industries and academic programs, including those leading to degrees in business administration (MBA), public health (MPH), and public administration (MPA). If you follow the advice in this book, the graphs you create for reports, presentations, posters, or publications will be more informative and more easily understo
Use Excel 2013’s radically revamped charting and graphing tools to communicate more clearly, powerfully, and quickly... so you drive your message home, and get the decisions and actions you’re looking for! This book reveals data visualization techniques you won’t find anywhere else and shows you how to use Excel 2013 to create designer-quality charts and graphs that stand out from the crowd. It will help you make the most of new features ranging from Power View to Recommended Charts, and instantly share your insights with anyone, anywhere–even on the Web and social networks. Learning advanced Excel techniques has never been easier. You’ll find simple, step-by-step instructions, real-world examples and case studies, and more than a dozen YouTube videos, straight from MrExcel! • Create stunning data visualizations instantly with Excel 2013’s new Recommended Charts • Use charts to instantly reveal trends, differences, and relationships • Map your data with Excel 2013, MapPoint, and the new GeoFlow add-in • Quickly generate combo charts that once required complex, frustrating procedures • Use sparklines to imbue worksheets with more context and insight • Highlight and clarify the meaning of data with DataBars, color scales, icon sets, and other conditional formatting tools • Post charts to Facebook, Twitter, or LinkedIn, directly from Excel • Build stock charts that help you make smarter investments • Solve “non-standard” problems such as noncontiguous data or custom data sequences • Generate new charts automatically with Excel VBA • Uncover visual tricks that people use to lie with Excel About MrExcel Library: Every book in the MrExcel Library pinpoints a specific set of crucial Excel tasks and presents focused skills and examples for performing them rapidly and effectively. Selected by Bill Jelen, Microsoft Excel MVP and mastermind behind the leading Excel solutions website MrExcel.com, these books will: • Dramatically increase your productivity–saving you 50 hours a year or more • Present proven, creative strategies for solving real-world problems • Show you how to get great results, no matter how much data you have • Help you avoid critical mistakes that even experienced users make
Influence action through data! This is not a book. It is a one-of-a-kind immersive learning experience through which you can become—or teach others to be—a powerful data storyteller. Let’s practice! helps you build confidence and credibility to create graphs and visualizations that make sense and weave them into action-inspiring stories. Expanding upon best seller storytelling with data’s foundational lessons, Let’s practice! delivers fresh content, a plethora of new examples, and over 100 hands-on exercises. Author and data storytelling maven Cole Nussbaumer Knaflic guides you along the path to hone core skills and become a well-practiced data communicator. Each chapter includes: ● Practice with Cole: exercises based on real-world examples first posed for you to consider and solve, followed by detailed step-by-step illustration and explanation ● Practice on your own: thought-provoking questions and even more exercises to be assigned or worked through individually, without prescribed solutions ● Practice at work: practical guidance and hands-on exercises for applying storytelling with data lessons on the job, including instruction on when and how to solicit useful feedback and refine for greater impact The lessons and exercises found within this comprehensive guide will empower you to master—or develop in others—data storytelling skills and transition your work from acceptable to exceptional. By investing in these skills for ourselves and our teams, we can all tell inspiring and influential data stories!
Don't simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it!
Information visualization is a language. Like any language, it can be used for multiple purposes. A poem, a novel, and an essay all share the same language, but each one has its own set of rules. The same is true with information visualization: a product manager, statistician, and graphic designer each approach visualization from different perspectives. Data at Work was written with you, the spreadsheet user, in mind. This book will teach you how to think about and organize data in ways that directly relate to your work, using the skills you already have. In other words, you don’t need to be a graphic designer to create functional, elegant charts: this book will show you how. Although all of the examples in this book were created in Microsoft Excel, this is not a book about how to use Excel. Data at Work will help you to know which type of chart to use and how to format it, regardless of which spreadsheet application you use and whether or not you have any design experience. In this book, you’ll learn how to extract, clean, and transform data; sort data points to identify patterns and detect outliers; and understand how and when to use a variety of data visualizations including bar charts, slope charts, strip charts, scatter plots, bubble charts, boxplots, and more. Because this book is not a manual, it never specifies the steps required to make a chart, but the relevant charts will be available online for you to download, with brief explanations of how they were created.
Information, no matter how important, cannot speak for itself. To tell its story, it relies on us to give it a clear voice. No information is more critical than quantitative data ... numbers that reveal what's happening, how our organizations are performing, and opportunities to do better. Numbers are usually presented in tables and graphs, but few are properly designed, resulting not only in poor communication, but at times in miscommunication. This is a travesty, because the skills needed to present quantitative information effectively are simple to learn. Good communication doesn't just happen; it is the result of good design.
Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.
A leading data visualization expert explores the negative—and positive—influences that charts have on our perception of truth. Today, public conversations are increasingly driven by numbers. While charts, infographics, and diagrams can make us smarter, they can also deceive—intentionally or unintentionally. To be informed citizens, we must all be able to decode and use the visual information that politicians, journalists, and even our employers present us with each day. Demystifying an essential new literacy for our data-driven world, How Charts Lie examines contemporary examples ranging from election result infographics to global GDP maps and box office record charts, as well as an updated afterword on the graphics of the COVID-19 pandemic.
Summary Visualizing Graph Data teaches you not only how to build graph data structures, but also how to create your own dynamic and interactive visualizations using a variety of tools. This book is loaded with fascinating examples and case studies to show you the real-world value of graph visualizations. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Assume you are doing a great job collecting data about your customers and products. Are you able to turn your rich data into important insight? Complex relationships in large data sets can be difficult to recognize. Visualizing these connections as graphs makes it possible to see the patterns, so you can find meaning in an otherwise over-whelming sea of facts. About the Book Visualizing Graph Data teaches you how to understand graph data, build graph data structures, and create meaningful visualizations. This engaging book gently introduces graph data visualization through fascinating examples and compelling case studies. You'll discover simple, but effective, techniques to model your data, handle big data, and depict temporal and spatial data. By the end, you'll have a conceptual foundation as well as the practical skills to explore your own data with confidence. What's Inside Techniques for creating effective visualizations Examples using the Gephi and KeyLines visualization packages Real-world case studies About the Reader No prior experience with graph data is required. About the Author Corey Lanum has decades of experience building visualization and analysis applications for companies and government agencies around the globe. Table of Contents PART 1 - GRAPH VISUALIZATION BASICS Getting to know graph visualization Case studies An introduction to Gephi and KeyLines PART 2 VISUALIZE YOUR OWN DATA Data modeling How to build graph visualizations Creating interactive visualizations How to organize a chart Big data: using graphs when there's too much data Dynamic graphs: how to show data over time Graphs on maps: the where of graph visualization
The essential characteristic of a dynamic graphical method is the direct manipulation of elements of a graph on a computer screen, which in high-performance implementations, the elements change virtually instantaneously on the screen. This book contains a collection of papers about dynamic graphics dating from the late 1960s to 1988. Although technology has advanced considerably, the fundamental ideas about basic graphical principles and data-analytic goals are still relevant today.